Semiconductor Biosensor Base Calling from Multi-Cluster Pixel Signals
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Solution Overview
Problem
Conventional solid-state imaging systems for biological or chemical analysis are limited by their ability to detect only one cluster per sensor, leading to low throughput and high costs due to the constraints of pixel density, which is a function of pixel pitch, making it difficult to efficiently analyze large nucleic acid arrays used in genotyping, expression, or sequencing analyses.
Innovation Solution
The system employs a biosensor with an array of sensors that can detect multiple clusters per pixel area by using two illumination stages to differentiate between nucleotide bases A, C, T, and G, and a signal processor that maps pixel signals into bins to classify results, allowing for the identification of nucleotide bases in multiple clusters using a shared sensor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional Sanger sequencing or pyrosequencing methods are used, then sequencing can be performed, but the throughput is limited and cost per base is high
Solution Approach 1:
The invention divides the sequencing task into parallel independent reactions occurring on individual wells of a microtiter plate. Each well contains a separate DNA template and performs simultaneous sequencing by synthesis with all four dNTPs, enabling thousands of sequences to be generated in parallel rather than sequentially as in traditional methods.
Solution Approach 2:
The invention replaces traditional optical detection systems with semiconductor-based detection using ion-sensitive field-effect transistors (ISFETs) or similar devices. This substitution enables electrical detection of nucleotide incorporation events, providing higher sensitivity, faster readout, and the ability to detect multiple nucleotide types simultaneously through frequency modulation.
2Measurement precision
If traditional optical detection methods are used for sequencing, then nucleotide incorporation can be detected, but the sensitivity is insufficient and background noise is high
Solution Approach 1:
The invention replaces optical detection with electrical detection using ion-sensitive field-effect transistors (ISFETs) or similar semiconductor devices. This substitution provides significantly higher sensitivity because electrical signals from single-molecule nucleotide incorporation events can be detected directly without the background noise inherent in optical systems. The semiconductor-based detectors can resolve individual incorporation events with minimal background interference.
Solution Approach 2:
The invention introduces an intermediary layer between the DNA polymerase reaction and the detection system. The intermediary is an ion-sensitive membrane or layer on the semiconductor detector that converts ionic changes during nucleotide incorporation into electrical signals. This intermediary enhances signal transduction while filtering out background noise, enabling precise detection of single-nucleotide events.
3Productivity
If parallel sequencing reactions are implemented, then throughput increases, but reagent consumption and well-to-well variation increase
Solution Approach 1:
The invention merges multiple sequencing reactions into a single microtiter plate format, where all reactions share common reagent reservoirs and are performed under identical environmental conditions. This merging approach ensures that all wells receive the same concentrations of dNTPs, buffer components, and other reagents, eliminating well-to-well variation caused by reagent preparation differences while maintaining high parallel throughput.
Solution Approach 2:
The invention creates a universal platform where a single microtiter plate setup can perform thousands of identical sequencing reactions simultaneously. The standardized well format, common reagent distribution system, and uniform detection approach make the system universally applicable while ensuring consistent performance across all parallel reactions, reducing variability inherent in individual reaction setups.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly increases the throughput of nucleic acid analysis by enabling the detection of multiple clusters per sensor, reducing sequencing time and costs, while maintaining accuracy through advanced signal processing algorithms.
Implementation Method 1
semiconductor-based detection
Data Source
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AI summary
A biosensor (300) for base calling is provided. The biosensor (300) comprises a sampling device, which includes a sample surface (334) that has an array of pixel areas (306', 308', 310', 312', 314') and a solid-state imager (322) that has an array of sensors (306, 308, 310, 312, 314). Each sensor (306, 308, 310, 312, 314) generates pixel signals in each base calling cycle. Each pixel signal represents light gathered in one base calling cycle from one or more clusters (306A, 306B; 308A, 308B; 310A, 310B; 312A, 312B; 314A, 314B) in a corresponding pixel area (306', 308', 310', 312', 314') of the sample surface (334). The biosensor (300) further comprises a signal processor configured for connection to the sampling device. The signal processor receives and processes the pixel signals from the sensors (306, 308, 310, 312, 314) for base calling in a base calling cycle, and uses the pixel signals from fewer sensors (306, 308, 310, 312, 314) than a number of clusters (306A, 306B; 308A, 308B; 310A, 310B; 312A, 312B; 314A, 314B) base called in the base calling cycle. Pixel signals from the fewer sensors (306, 308, 310, 312, 314) include at least one pixel signal representing light gathered from at least two clusters (306A, 306B; 308A, 308B; 310A, 310B; 312A, 312B; 314A, 314B) in the corresponding pixel area (306', 308', 310', 312', 314').